Quelle: Advances in Complex Systems, 21 (2018) 3-4, S 1-23
Inhalt: Scientific collaborations shape ideas as well as innovations and are both the substrate for, and the outcome of, academic careers. Recent studies show that gender inequality is still present in many scientific practices ranging from hiring to peer-review processes and grant applications. In this work, we investigate gender-specific differences in collaboration patterns of more than one million computer scientists over the course of 47 years. We explore how these patterns change over years and career ages and how they impact scientific success. Our results highlight that successful male and female scientists reveal the same collaboration patterns: compared to scientists in the same career age, they tend to collaborate with more colleagues than other scientists, seek innovations as brokers and establish longer-lasting and more repetitive collaborations. However, women are on average less likely to adopt the collaboration patterns that are related with success, more likely to embed into ego networks devoid of structural holes, and they exhibit stronger gender homophily as well as a consistently higher dropout rate than men in all career ages.
Quelle: ACM Web Science Conference (WebSci '17); New York, 2017. S 83-92
Inhalt: Previous research has shown the existence of gender biases in the depiction of professions and occupations in search engine results. Such an unbalanced presentation might just as likely occur on Wikipedia, one of the most popular knowledge resources on the Web, since the encyclopedia has already been found to exhibit such tendencies in past studies. Under this premise, our work assesses gender bias with respect to the content of German Wikipedia articles about professions and occupations along three dimensions: used male vs. female titles (and redirects), included images of persons, and names of professionals mentioned in the articles. We further use German labor market data to assess the potential misrepresentation of a gender for each specific profession. Our findings in fact provide evidence for systematic over-representation of men on all three dimensions. For instance, for professional fields dominated by females, the respective articles on average still feature almost two times more images of men; and in the mean, 83% of the mentioned names of professionals were male and only 17% female.
It's a Man's Wikipedia? Assessing Gender Inequality in an Online Encyclopedia
Autor/in:
Wagner, Claudia; Garcia, David; Jadidi, Mohsen; Strohmaier, Markus
Quelle: Association for the Advancement of Artificial Intelligence (AAAI); International AAAI Conference on Weblogs and Social Media; Palo Alto, CA, 2015. S 454-463
Inhalt: Wikipedia is a community-created encyclopedia that contains information about notable people from different countries, epochs and disciplines and aims to document the world's knowledge from a neutral point of view. However, the narrow diversity of the Wikipedia editor community has the potential to introduce systemic biases such as gender biases into the content of Wikipedia. In this paper we aim to tackle a sub problem of this larger challenge by presenting and applying a computational method for assessing gender bias on Wikipedia along multiple dimensions. We find that while women on Wikipedia are covered and featured well in many Wikipedia language editions, the way women are portrayed starkly differs from the way men are portrayed. We hope our work contributes to increasing awareness about gender biases online, and in particular to raising attention to the different levels in which gender biases can manifest themselves on the web.